Algorithmically curated lies: How search engines handle misinformation about U.S. biolabs in Ukraine

Abstract

The growing volume of online content prompts the need for adopting algorithmic systems for curating information. These systems range from web search engines to recommender systems and are integral for helping users stay informed about important societal developments. However, the algorithmic information curation systems (AICSs) are known to be subject to different forms of malperformance which make them vulnerable to possible manipulation, especially in the context of online news distribution. The risk of manipulation is particularly prominent when AICSs have to deal with information about false claims that underpin propaganda campaigns of authoritarian regimes. Using as a case study the Russian disinformation campaign concerning U.S. biolabs in Ukraine, we investigate how one of the most commonly used forms of AICSs—i.e. web search engines—curate misinformation-related content. For this aim, we conduct virtual agent-based algorithm audits of Google, Bing, and Yandex search outputs. Our findings highlight the troubling performance of search engines. Even though some search engines, like Google, were less likely to return false claims, across all languages and locations, the three search engines still mentioned or promoted a considerable share of false content (33% on Google, 44% on Bing, and 70% on Yandex). We also find significant disparities in misinformation exposure based on the language of search, with all search engines presenting a higher number of false stories in Russian. Location matters as well, with users from Germany being more likely to be exposed to search results promoting false information. These observations show that AICSs may be vulnerable to manipulation, in particular in the case of unfolding propaganda campaigns, and we stress the importance of monitoring these systems’ performance to prevent it.

The authors' abstract, as published at the source. Big Data & Society, 2026 · DOI ↗